AI role · Open offer

LLM Engineer — enterprise delivery

Proxym Group

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: Les Berges du Lac II, Tunis, Tunis 10530, Tunisia · Hybrid
Compensation: EUR 30k–45k/year + bonus
Experience level: Senior
Team: GenAI practice
Benefits & perks

About this role

What the team is looking for and how this position fits.

Proxym Group is hiring a Senior LLM Engineer — enterprise delivery on the GenAI practice team (Hybrid · Tunis, Tunisia). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Proxym Group delivers digital transformation and GenAI projects for EU and MENA clients from Tunis.

LLM Engineer: enterprise RAG, agents, eval gates, and MLOps handover.

Missions

Client delivery sprints with security and data residency reviews.
Reusable eval templates for French/English copilots.

Stack & environment

Python, LangChain, Azure, Docker.

What we look for

Consulting + LLM delivery; 3+ years.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
OpenAI API

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.
AzureTool
Regular use of Azure in the LLM & generative AI stack—configuration, debugging, and team conventions.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Client RAG/agent delivery with eval gates and handover docs.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, OpenAI API, MLOps, and Docker.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Tunis, Tunisia)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

Apply

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What the employer asked for

Client RAG/agent delivery with eval gates and handover docs.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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